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title: Cifar10 Classification | |
emoji: 🤗 | |
colorFrom: red | |
colorTo: pink | |
sdk: streamlit | |
sdk_version: 1.33.0 | |
app_file: app.py | |
pinned: false | |
license: apache-2.0 | |
Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference | |
### To access the app, follow these steps: | |
Step 1: Access the app directly on the link (This does not use the FastAPI endpoints): | |
[https://huggingface.co/spaces/TrishanuDas/cifar10_classification](https://huggingface.co/spaces/TrishanuDas/cifar10_classification) | |
Step 2: Use the Streamlit app via the FastAPI endpoint. | |
- Run the FastAPI server on any instance using the following command: | |
``` | |
uvicorn api_endpoint:app --reload --host <host_name> | |
``` | |
- Change the HOST variable on the `app_with_fastapi.py` file. | |
- Execute the app_with_fastapi.py file using the following command: | |
``` | |
streamlit run app_with_fastapi.py | |
``` | |
### Files | |
The following files are present in this repository: | |
- `app.py`: The main Streamlit app file to run directly. | |
- `requirements.txt`: The list of Python dependencies required by the app. | |
- `model.py`: Contains the code for loading and using the pre-trained model. | |
- `app_endpoint.py`: Contains api_endpoint for the prediction. | |
- `app_with_fastapi.py`: Contains the code for the Streamlit app with FastAPI endpoint. | |